Earlier this year, we explored how NRF 2026 signaled the arrival of agentic commerce – a future where AI doesn’t simply help customers shop but increasingly researches products, compares vendors and, in some cases, completes purchases on their behalf. That shift has implications far beyond retailers. It also creates a new advisory opportunity for managed services providers (MSPs).
For years, digital visibility revolved around search engine optimization (SEO). Businesses focused on ranking highly in Google, driving website traffic and converting human visitors into customers.
That approach still matters, but it’s no longer the whole story.
Today’s large language models (LLMs), AI assistants and answer engines – including ChatGPT, Google AI Overviews, Microsoft Copilot and Perplexity – are changing how buyers discover products and services. Rather than returning a list of links, they increasingly synthesize information from multiple trusted sources into a direct answer. In many cases, customers may never visit a traditional search results page before making a purchasing decision.
For MSPs, that means helping clients optimize for AI discovery – not just traditional search rankings – may soon become as important as maintaining reliable networks or securing endpoints.
From SEO to GEO
This emerging discipline is commonly known as generative engine optimization (GEO).
Unlike traditional SEO, which focuses on keywords, backlinks and page rankings, GEO emphasizes whether AI systems can accurately understand, verify and confidently reference a company’s information.
Recent research illustrates why this matters. Omnibound found that 83% of citations generated by AI search engines originated from pages outside Google’s traditional top 10 organic search results. In other words, authoritative, well-structured information often matters more than conventional ranking position when AI systems generate answers.
For clients, that means winning the AI recommendation may become just as valuable as winning the first page of Google.
Why MSPs should care
Most organizations aren’t thinking about AI discoverability yet.
That’s an opportunity.
MSPs already manage many of the systems that determine whether AI platforms can successfully interpret and recommend a business:
• Websites
• E-commerce platforms
• Product information management (PIM) systems
• Content management systems
• APIs
• Cloud infrastructure
• Security and availability
Viewed through that lens, AI discoverability isn’t simply a marketing issue. It’s becoming another element of digital infrastructure.
If product information is inconsistent, APIs are unreliable or structured data is missing, AI systems may struggle to understand – or recommend – a client’s business.
What AI systems look for
Unlike traditional web browsers, AI systems consume structured, machine-readable information. The easier it is for models to verify facts, understand relationships and access current information, the more confidently they can reference a company in their responses.
That means MSPs should encourage clients to invest in several foundational capabilities.
1Structured data
Schema markup – particularly JSON-LD – helps search engines and AI models understand products, services, organizations, reviews, locations and frequently asked questions.
Comprehensive, accurate schema provides the factual context AI systems increasingly rely on.
2Reliable APIs
Many modern AI applications retrieve live information rather than relying solely on indexed web pages. Product availability, pricing, inventory and business information should be exposed through secure, well-documented APIs whenever practical.
Slow, unreliable or inconsistent APIs can make it more difficult for AI systems and third-party applications to retrieve accurate information.
3Clean, consistent content
AI models reward clarity.
Duplicate information, conflicting product descriptions, inconsistent pricing and outdated content reduce confidence and increase the likelihood that another source will be cited instead.
4Strong technical foundations
Fast websites, secure infrastructure, high availability and clean site architecture continue to matter – not only for human visitors but also for AI systems that regularly crawl and evaluate content.
Traditional SEO best practices remain important. GEO builds upon them rather than replacing them.
Five AI discoverability questions every MSP should ask clients
As AI-assisted buying becomes more common, MSPs should begin asking questions that few businesses have considered:
1. Can AI systems accurately identify your products, services and locations?
2. Is your website using comprehensive structured data such as JSON-LD?
3. Are pricing, inventory and product information available in machine-readable formats where appropriate?
4. Are your APIs reliable, secure and consistently available?
5. If someone asks ChatGPT or another AI assistant about your industry, would your company be confidently recommended?
These conversations naturally lead beyond infrastructure support into higher-value business consulting.
A new recurring revenue opportunity
Many MSPs already perform security assessments, cloud readiness evaluations and compliance reviews.
AI discoverability is a logical extension.
An AI Discoverability Assessment might include:
- Reviewing structured data implementation.
- Evaluating website architecture.
- Assessing API health and availability.
- Identifying inconsistent or outdated content.
- Validating schema markup.
- Reviewing AI search visibility.
- Prioritizing technical improvements that improve machine readability.
Rather than waiting for clients to ask about AI optimization, MSPs can proactively demonstrate how emerging search experiences may affect future customer acquisition.
Those findings can lead to implementation projects, ongoing monitoring services and recurring optimization engagements.
Looking beyond search
The transition from SEO to GEO doesn’t mean traditional search is disappearing.
It means businesses increasingly need to optimize for both human visitors and AI systems.
That’s especially important in retail, distribution and hospitality, where purchasing decisions are becoming increasingly influenced by AI-generated recommendations.
Just as cybersecurity evolved from an optional service into a core business requirement, AI discoverability has the potential to become another strategic advisory practice for MSPs.
The firms that begin developing these capabilities today won’t simply help clients rank higher in search results. They’ll help ensure clients remain visible in a future where AI increasingly decides what customers see – and what they never discover.
